The application of probabilistic climate change projections: a comparison of methods of handling uncertainty applied to UK irrigation reservoir design

2014 ◽  
Vol 5 (4) ◽  
pp. 652-666 ◽  
Author(s):  
Michael Green ◽  
Edward Keith Weatherhead
Keyword(s):  
Climate Change ◽  
Probability Distributions ◽  
Latin Hypercube Sampling ◽  
Probabilistic Methods ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Irrigation Reservoir ◽  
Inadequate Sample Size ◽  
Reservoir Design ◽  
The Impact

Climate projections are increasingly being presented in terms of uncertainties and probability distributions rather than median or ‘most-likely’ values. The current national UK climate change projections, UKCP09, provide 10,000 probabilistic projections (PP) and 11 spatially coherent projections (11SCP) for three future emission scenarios. In contrast, previous iterations such as UKCIP02 provided only a single ‘most-likely’ (deterministic) projection for each. This move from deterministic to probabilistic methods of communicating climate change information, whilst increasing the wealth of the data, complicates the process of adaptation planning by communicating extra uncertainty to the public and decision-makers. This paper examines the application of probabilistic climate change projections and explores the impact of uncertainty on decision-making, using a case study of irrigation reservoir design at three sites in the UK. The implications of sub-sampling the PP using both simple random and Latin-hypercube sampling are also explored. The study found that the choice of dataset has a much larger impact on irrigation reservoir design than emission uncertainty. The study confirmed the dangers of inadequate sample size, particularly when applying decision criteria based on extreme events, and found that more advanced stratified sampling techniques did not noticeably improve the reproducibility of decision outcomes.

Is Institutional Democracy a Good Proxy for Model Independence?

2016 ◽  
Vol 29 (23) ◽  
pp. 8301-8316 ◽  
Author(s):  
Martin Leduc ◽  
René Laprise ◽  
Ramón de Elía ◽  
Leo Šeparović
Keyword(s):  
Climate Change ◽  
Model Comparison ◽  
Climate Models ◽  
Regional Climate ◽  
Burden Of Proof ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Cross Model ◽  
Structural Differences ◽  
The Impact

Abstract Climate models developed within a given research group or institution are prone to share structural similarities, which may induce resembling features in their simulations of the earth’s climate. This assertion, known as the “same-center hypothesis,” is investigated here using a subsample of CMIP3 climate projections constructed by retaining only the models originating from institutions that provided more than one model (or model version). The contributions of individual modeling centers to this ensemble are first presented in terms of climate change projections. A metric for climate change disagreement is then defined to analyze the impact of typical structural differences (such as resolution, parameterizations, or even entire atmosphere and ocean components) on regional climate projections. This metric is compared to a present climate performance metric (correlation of error patterns) within a cross-model comparison framework in terms of their abilities to identify the same-center models. Overall, structural differences between the pairs of same-center models have a stronger impact on climate change projections than on how models reproduce the observed climate. The same-center criterion is used to detect agreements that might be attributable to model similarities and thus that should not be interpreted as implying greater confidence in a given result. It is proposed that such noninformative agreements should be discarded from the ensemble, unless evidence shows that these models can be assumed to be independent. Since this burden of proof is not generally met by the centers participating in a multimodel ensemble, the authors propose an ensemble-weighting scheme based on the assumption of institutional democracy to prevent overconfidence in climate change projections.

Balanced subsampling of future regional climate ensembles of opportunity

2020 ◽  
Author(s):  
Jesús Fernández ◽  
María Dolores Frías
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Regional Climate ◽  
National Level ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Modelling ◽  
Model Intercomparison ◽  
Climate Change Projections ◽  
The Impact

<p>International model intercomparison initiatives, such as CORDEX or CMIP5, along with several relatively recent projects at international and national level, provide a wealth of model simulations of future regional climate. In a recent work, Fernandez et al (2019) collected 196 different future climate change projections over Spain, considering data from ENSEMBLES, ESCENA, EURO- and Med-CORDEX, along with their driving global climate projections from CMIP3 and CMIP5. This ensemble mixed different multi-model initiatives in an ensemble of opportunity, in the sense that it does not respond to any scientific design beyond the exploration of multi-model uncertainty. This ensemble of opportunity is not only the result of the mixture of different initiatives, but also responds to the lack of a balanced experimental design within most of the initiatives. Many of the initiatives -especially those unfunded, such as CORDEX- are carried out on a voluntary basis, with no strong constraint in the global climate models (GCMs) used as boundary conditions or in the number of contributing members per regional climate model (RCM).</p><p>Fernandez et al (2019) found in this ensemble a strong influence of the driving GCM on the regional climate change signal, along with favored GCMs, selected by many regional climate modelling groups to the detriment of GCMs publishing their output later or not at all. In this work, we quantitatively assess the impact of unbalanced GCM-RCM ensembles. For this purpose, we subsampled the ensemble of opportunity to obtain balanced sets of members according to different “what-if” situations: What if all RCMs had contributed a single member to the ensemble? What if each GCM had been dynamically downscaled only once? What if a given GCM/RCM had not contributed to the ensemble? For each hypothesis, there are a number of alternative sub-ensembles, which are used to evaluate uncertainty.</p><p><strong>Acknowledgement:</strong></p><p>This work is partially funded by the Spanish government through MINECO/FEDER co-funded projects INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R). </p><p><strong>References:</strong></p><p>Fernández, J., et al. (2019) Consistency of climate change projections from multiple global and regional model intercomparison projects. Clim Dyn 52:1139. https://doi.org/10.1007/s00382-018-4181-8</p>

scholarly journals High resolution climate change projections for the Pyrenees region

2020 ◽  
Vol 17 ◽  
pp. 191-208
Author(s):  
María P. Amblar-Francés ◽  
Petra Ramos-Calzado ◽  
Jorge Sanchis-Lladó ◽  
Alfonso Hernanz-Lázaro ◽  
María C. Peral-García ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
21St Century ◽  
Statistical Downscaling ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Climate Conditions ◽  
The Impact

Abstract. The Pyrenees, located in the transition zone of Atlantic and Mediterranean climates, constitute a paradigmatic example of mountains undergoing rapid changes in environmental conditions, with potential impact on the availability of water resources, mainly for downstream populations. High-resolution probabilistic climate change projections for precipitation and temperature are a crucial element for stakeholders to make well-informed decisions on adaptation to new climate conditions. In this line, we have generated high–resolution climate projections for 21st century by applying two statistical downscaling methods (regression for max and min temperatures, and analogue for precipitation) over the Pyrenees region in the frame of the CLIMPY project over a new high-resolution (5 km × 5 km) observational grid using 24 climate models from CMIP5. The application of statistical downscaling to such a high resolution observational grid instead of station data partially circumvent the problems associated to the non-uniform distribution of observational in situ data. This new high resolution projections database based on statistical algorithms complements the widely used EUROCORDEX data based on dynamical downscaling and allows to identify features that are dependent on the particular downscaling method. In our analysis, we not only focus on maximum and minimum temperatures and precipitation changes but also on changes in some relevant extreme indexes, being 1986–2005 the reference period. Although climate models predict a general increase in temperature extremes for the end of the 21st century, the exact spatial distribution of changes in temperature and much more in precipitation remains uncertain as they are strongly model dependent. Besides, for precipitation, the uncertainty associated to models can mask – depending on the zones- the signal of change. However, the large number of downscaled models and the high resolution of the used grid allow us to provide differential information at least at massif level. The impact of the RCP becomes significant for the second half of the 21st century, with changes – differentiated by massifs – of extreme temperatures and analysed associated extreme indexes for RCP8.5 at the end of the century.

scholarly journals Urban Geometry Optimization to Mitigate Climate Change: Towards Energy-Efficient Buildings

2020 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Hatem Mahmoud ◽  
Ayman Ragab
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Thermal Efficiency ◽  
Energy Demand ◽  
Building Blocks ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Urban Geometry ◽  
Outdoor Spaces ◽  
The Impact

The density of building blocks and insufficient greenery in cities tend to contribute dramatically not only to increased heat stress in the built environment but also to higher energy demand for cooling. Urban planners should, therefore, be conscious of their responsibility to reduce energy usage of buildings along with improving outdoor thermal efficiency. This study examines the impact of numerous proposed urban geometry cases on the thermal efficiency of outer spaces as well as the energy consumption of adjacent buildings under various climate change scenarios as representative concentration pathways (RCP) 4.5 and 8.5 climate projections for New Aswan city in 2035. The investigation was performed at one of the most underutilized outdoor spaces on the new campus of Aswan University in New Aswan city. The potential reduction of heat stress was investigated so as to improve the thermal comfort of the investigated outdoor spaces, as well as energy savings based on the proposed strategies. Accordingly, the most appropriate scenario to be adopted to cope with the inevitable climate change was identified. The proposed scenarios were divided into four categories of parameters. In the first category, shelters partially (25–50% and 75%) covering the streets were used. The second category proposed dividing the space parallel or perpendicular to the existing buildings. The third category was a hybrid scenario of the first and second categories. In the fourth category, a green cover of grass was added. A coupling evaluation was applied utilizing ENVI-met v4.2 and Design-Builder v4.5 to measure and improve the thermal efficiency of the outdoor space and reduce the cooling energy. The results demonstrated that it is better to cover outdoor spaces with 50% of the overall area than transform outdoor spaces into canyons.

Soil Type Modifies the Impacts of Warming and Snow Exclusion on Carbon and Nutrient Losses

2021 ◽  
Author(s):  
Stephanie M. Juice ◽  
Paul G. Schaberg ◽  
Alexandra M. Kosiba ◽  
Carl E. Waite ◽  
Gary J. Hawley ◽  
...  
Keyword(s):  
Climate Change ◽  
Nutrient Cycling ◽  
Soil Type ◽  
Soil Characteristics ◽  
Nutrient Loss ◽  
Climate Projections ◽  
Nutrient Losses ◽  
N Losses ◽  
Total N ◽  
The Impact

Abstract The varied and wide-reaching impacts of climate change are occurring across heterogeneous landscapes. Despite the known importance of soils in mediating biogeochemical nutrient cycling, there is little experimental evidence of how soil characteristics may shape ecosystem response to climate change. Our objective was to clarify how soil characteristics modify the impact of climate changes on carbon and nutrient leaching losses in temperate forests. We therefore conducted a field-based mesocosm experiment with replicated warming and snow exclusion treatments on two soils in large (2.4 m diameter), in-field forest sapling mesocosms. We found that nutrient loss responses to warming and snow exclusion treatments frequently varied substantially by soil type. Indeed, in some cases, soil type nullified the impact of a climate treatment. For example, warming and snow exclusion increased nitrogen (N) losses on fine soils by up to four times versus controls, but these treatments had no impact on coarse soils. Generally, the coarse textured soil, with its lower soil-water holding capacity, had higher nutrient losses (e.g., 12-17 times more total N loss from coarse than fine soils), except in the case of phosphate, which had consistently higher losses (23-58%) from the finer textured soil. Furthermore, the mitigation of nutrient loss by increasing tree biomass varied by soil type and nutrient. Our results suggest that potentially large biogeochemical responses to climate change are strongly mediated by soil characteristics, providing further evidence of the need to consider soil properties in Earth system models for improving nutrient cycling and climate projections.

Structural safety and design under climate change

2019 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Structural Reliability ◽  
Greenhouse Gas Emission ◽  
Extreme Value ◽  
Structural Safety ◽  
Climate Projections ◽  
Climate Conditions ◽  
Impact Of Climate Change ◽  
The Impact

<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the consequences of this phenomenon could be much more complex and even apparently not coherent with the global trend of main climatic parameters, like for example, temperature, rainfalls, snowfalls and wind velocity.</p><p>In the paper, a general methodology is presented, aiming to evaluate the impact of climate change on structural design, as the result of variations of characteristic values of the most relevant climatic actions over time. The proposed procedure is based on the analysis of an ensemble of climate projections provided according a medium and a high greenhouse gas emission scenario. Factor of change for extreme value distribution’s parameters and return values are thus estimated in subsequent time windows providing guidance for adaptation of the current definition of structural loads.</p><p>The methodology is illustrated together with the outcomes obtained for snow, wind and thermal actions in Italy. Finally, starting from the estimated changes in extreme value parameters, the influence on the long-term structural reliability can be investigated comparing the resulting time dependent reliability with the reference reliability levels adopted in modern Structural codes.</p>

scholarly journals Impact of climate change on hydropower production in the Upper Danube

2021 ◽  
Author(s):  
Ignacio Martin Santos ◽  
Mathew Herrnegger ◽  
Hubert Holzmann
Keyword(s):  
Climate Change ◽  
Spatial Resolution ◽  
Transfer Functions ◽  
Danube River ◽  
Emission Scenarios ◽  
Hydropower Generation ◽  
Climate Change Projections ◽  
Impact Of Climate Change ◽  
The Future ◽  
The Impact

&lt;p&gt;In the last two decades, different climate downscaling initiatives provided climate scenarios for Europe. The most recent initiative, CORDEX, provides Regional Climate Model (RCM) data for Europe with a spatial resolution of 12.5 km, while the previous initiative, ENSEMBLES, had a spatial resolution of 25 km. They are based on different emission scenarios, Representative Concentration Pathways (RCPs) and Special Report on Emission Scenarios (SRES) respectively.&lt;/p&gt;&lt;p&gt;A study carried out by Stanzel et al. (2018) explored the hydrological impact and discharge projections for the Danube basin upstream of Vienna when using either CORDEX and ENSEMBLES data. This basin covers an area of 101.810&lt;sup&gt;&lt;/sup&gt;km&lt;sup&gt;2&lt;/sup&gt; with a mean annual discharge of 1923 m&lt;sup&gt;3&lt;/sup&gt;/s at the basin outlet. The basin is dominated by the Alps, large gradients and is characterized by high annual precipitations sums which provides valuable water resources available along the basin. Hydropower therefore plays an important role and accounts for more than half of the installed power generating capacity for this area. The estimation of hydropower generation under climate change is an important task for planning the future electricity supply, also considering the on-going EU efforts and the &amp;#8220;Green Deal&amp;#8221; initiative.&lt;/p&gt;&lt;p&gt;Taking as input the results from Stanzel et al. (2018), we use transfer functions derived from historical discharge and hydropower generation data, to estimate potential changes for the future. The impact of climate change projections of ENSEMBLE and CORDEX in respect to hydropower generation for each basin within the study area is determined. In addition, an assessment of the impact on basins dominated by runoff river plants versus basins dominated by storage plants is considered.&lt;/p&gt;&lt;p&gt;The good correlation between discharge and hydropower generation found in the historical data suggests that discharge projection characteristics directly affect the future expected hydropower generation. Large uncertainties exist and stem from the ensembles of climate runs, but also from the potential operation modes of the (storage) hydropower plants in the future.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Stanzel, P., Kling, H., 2018. From ENSEMBLES to CORDEX: Evolving climate change projections for Upper Danube River flow. J. Hydrol. 563, 987&amp;#8211;999. https://doi.org/10.1016/j.jhydrol.2018.06.057&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals What role will climate change play in EU agricultural markets? An integrated assessment taking into account carbon fertilization effects

2017 ◽  
Vol 15 (3) ◽  
pp. e0115 ◽  
Author(s):  
Pilar Martinez ◽  
María Blanco ◽  
Benjamin Van Doorslaer ◽  
Fabien Ramos ◽  
Andrej Ceglar
Keyword(s):  
Climate Change ◽  
Supply And Demand ◽  
Agricultural Markets ◽  
Climate Projections ◽  
Baseline Scenario ◽  
Market Uncertainty ◽  
Agricultural Market ◽  
Carbon Fertilization ◽  
Fertilization Effects ◽  
The Impact

Recent studies point to climate change being one of the long-term drivers of agricultural market uncertainty. To advance in the understanding of the influence of climate change on future agricultural market developments, we compared a baseline scenario for the year 2030 with alternative simulation scenarios that differ regarding: (1) emission scenarios; (2) climate projections; and (3) the consideration of carbon fertilization effects on crop growth. For each simulation scenario, the CAPRI model provides global and EU-wide impacts of climate change on agricultural markets. Results showed that climate change would considerably affect agrifood markets up to 2030. Nevertheless, market-driven adaptation strategies (production intensification, trade adjustments) would soften the impact of yield shocks on supply and demand. As a result, regional changes in production would be lower than foreseen by other studies focused on supply effects.

scholarly journals Climate Perspectives in the Intra–Americas Seas

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 959
Author(s):  
Ana María Durán-Quesada ◽  
Rogert Sorí ◽  
Paulina Ordoñez ◽  
Luis Gimeno
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Large Scale ◽  
Negative Impact ◽  
Current Knowledge ◽  
Regional Climate ◽  
Climate Projections ◽  
Economic Activities ◽  
Weather And Climate ◽  
The Impact

The Intra–Americas Seas region is known for its relevance to air–sea interaction processes, the contrast between large water masses and a relatively small continental area, and the occurrence of extreme events. The differing weather systems and the influence of variability at different spatio–temporal scales is a characteristic feature of the region. The impact of hydro–meteorological extreme events has played a huge importance for regional livelihood, having a mostly negative impact on socioeconomics. The frequency and intensity of heavy rainfall events and droughts are often discussed in terms of their impact on economic activities and access to water. Furthermore, future climate projections suggest that warming scenarios are likely to increase the frequency and intensity of extreme events, which poses a major threat to vulnerable communities. In a region where the economy is largely dependent on agriculture and the population is exposed to the impact of extremes, understanding the climate system is key to informed policymaking and management plans. A wealth of knowledge has been published on regional weather and climate, with a majority of studies focusing on specific components of the system. This study aims to provide an integral overview of regional weather and climate suitable for a wider community. Following the presentation of the general features of the region, a large scale is introduced outlining the main structures that affect regional climate. The most relevant climate features are briefly described, focusing on sea surface temperature, low–level circulation, and rainfall patterns. The impact of climate variability at the intra–seasonal, inter–annual, decadal, and multi–decadal scales is discussed. Climate change is considered in the regional context, based on current knowledge for natural and anthropogenic climate change. The present challenges in regional weather and climate studies have also been included in the concluding sections of this review. The overarching aim of this work is to leverage information that may be transferred efficiently to support decision–making processes and provide a solid foundation on regional weather and climate for professionals from different backgrounds.

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

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